JakobStenseke/Artificial-Chemotaxis-in-Dynamic-Environments

Artificial agents developing chemotaxis using probabilistic spiking perceptrons

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Experimental

This project simulates how simple artificial organisms might learn to find food or avoid poisons in a changing environment. It takes basic simulated agents that can move forward or rotate and a moving food source as input. It then shows how these agents, through a basic evolutionary process, can develop the ability to navigate towards the food source, providing insights for researchers in fields like artificial biology and evolutionary computing.

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Use this if you are a researcher interested in observing how very simple artificial agents can develop adaptive behaviors like chemotaxis in dynamic, simulated biological environments.

Not ideal if you are looking for a complex, high-fidelity simulation of specific biological neural circuits or for a tool to implement advanced deep learning techniques.

artificial-life-simulation evolutionary-computation chemotaxis-modeling biological-inspiration agent-behavior-studies
No License Stale 6m No Package No Dependents
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Language

C#

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Last pushed

Feb 13, 2019

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